Benjamin Squire modeled the SumoDB in #Neo4j and ran Eigenvector Centrality to find the most connected rikishi. The finding: rank does not always mean centrality. bit.ly/49IrvrF #Neo4j #GraphDataScience

🔮 Predict with Neo4j and Graph Data Science? Yes, it is possible (and it's not magic!) Henry Collie used Neo4j's link prediction to investigate the provenance of the Voynich Manuscript. By analyzing manuscript ownership patterns across thousands of medieval texts, we uncovered a fascinating candidate: Hartmann Schedel, a 15th-century physician and bibliophile with intriguing connections to Augsburg, cryptography, and mystical texts. Explore this compelling case study in how #GraphDataScience can surface hidden patterns in historical data. Is all about connections! bit.ly/4pksiUZ #Neo4j #graphdatabase

Connected Data London 2025: Final Call for Submissions - One week to go ⏳ Ready to share your knowledge with the world's most passionate data community? This is YOUR moment! 🌟 We're seeking leaders and innovators to showcase: 🔗 Knowledge Graphs transforming industries 🧠 Graph Analytics, Data Science & AI breakthroughs 🏗️ Graph Database success and caution stories 🎯 Semantic Technology implementations 📊 Real-world ontology applications If you are considering sharing your knowledge with the world's most passionate data community, we are highlighting topics we are interested in, and provide tips and inspiration 🌟 📌 Last minute submissions welcome! We did an initial analysis and assesment of submissions so far, and here's what we found out, along with some tips on where we'd like to see more submissions: * Most of our submissions so far are very technically advanced. We welcome more submissions aimed at beginners for our Educational track * We also welcome more Masterclass submissions. Masterclasses are harder to put together than Presentations. However, the engagement and connection built with the audience is unique * More use cases are always welcome - there's never too many of those! Looking for Inspiration? Check out related work by the CDL community: Building Trust In AI: Semantic Interoperability and Knowledge Graphs at the Rescue of LLMs by Jérémy Ravenel 2024.connected-data.london/t… Navigating Knowledge Graph Creation: A Practical Approach for Developers by Leah Miller youtube.com/watch?v=zs1xnszu… Introducing D3FEND: A Knowledge Graph of Cybersecurity Countermeasures by Peter Kaloroumakis youtube.com/watch?v=JQCO07KA… RDF and OWL : The powerful duo by Tara Raafat youtube.com/watch?v=zteyEk9L… Adding More Context to Machine Learning, Using Taxonomies and Knowledge Graphs by Ashleigh Faith youtube.com/watch?v=-y91g08q… What we offer: ✅ Platform to reach a global audience ✅ Free access pass for accepted speakers ✅ Expert program committee evaluation ✅ Community that's been connecting data, people & ideas since 2016 We are open to receiving: 📈 Presentations: Share your real-world use cases & innovative approaches 🛠️ Masterclasses: Teach hands-on skills attendees can use immediately Key Dates: 🗓️ Sept 1, 2025: Submission Deadline 🗓️ Sept 19, 2025: Acceptance Notification 🗓️ Nov 20-21, 2025: Event Days in London Join the community that helped pave the way for today's widespread recognition of graph technologies. Let's shape the next chapter together! Ready to make your mark? Check the Call for Submissions for topics of interest, submission process and evaluation criteria 👇 connected-data.london/call-f… #ConnectedData #CallForPapers #KnowledgeGraphs #GraphDataScience #GraphDatabase #SemanticTech #TechConference #DataCommunity #GraphTechnology #AIInnovation #DataScience #TechSpeaking #ConferenceSubmission #DataExperts #GraphAnalytics #Ontology #AI #GenAI #EmergingTech #SemTech

☺️Currently learning more about #graphdatascience and its #mathematics and its numerous usescases in real life for Social Network Analysis and much more : in my case Information Systems Urbanization 📖 "Dots and Lines" -"" - @Anthony_Bonato 🛒 goodreads.com/book/show/2146…

Connected Data London 2025: Call for Submissions is now open 🚀 Ready to share your knowledge with the world's most passionate data community? This is YOUR moment! 🌟 We're seeking leaders and innovators to showcase: 🔗 Knowledge Graphs transforming industries 🧠 Graph Analytics, Data Science & AI breakthroughs 🏗️ Graph Database success and caution stories 🎯 Semantic Technology implementations 📊 Real-world ontology applications What we offer: ✅ Platform to reach a global audience ✅ Free access pass for accepted presenters ✅ Expert program committee evaluation ✅ Community that's been connecting data, people & ideas since 2016 We are open to receiving: 📈 Presentations: Share your real-world use cases & innovative approaches 🛠️ Masterclasses: Teach hands-on skills attendees can use immediately Key Dates: 🗓️ Sept 1, 2025: Submission Deadline 🗓️ Sept 19, 2025: Acceptance Notification 🗓️ Nov 20-21, 2025: Event Days in London Join the community that helped pave the way for today's widespread recognition of graph technologies. Let's shape the next chapter together! Ready to make your mark? Check the our Call for Submissions for topics of interest, submission process and evaluation criteria 👇 connected-data.london/call-f… @pacoid @amyhodler @katsi111 @PAlexop @kurt_cagle @AshleighNFaith @Giuseppe_Futia @OraLassila @TheodoraPetkova @JuanSequeda @kvistgaard @MEVidalSerodio @cyberandy #ConnectedData #CallForPapers #KnowledgeGraphs #GraphDataScience #GraphDatabase #SemanticTech #TechConference #DataCommunity #GraphTechnology #AIInnovation #DataScience #TechSpeaking #ConferenceSubmission #DataExperts #GraphAnalytics #Ontology #AI #GenAI #EmergingTech #SemTech

Graph-Based Data Science: Hybrid AI meets data science process Python offers excellent libraries for working with graphs: semantic technologies, graph queries, interactive visualizations, graph algorithms, probabilistic graph inference, as well as embedding and other integrations with deep learning. However, most of these approaches share little common ground, nor do many of them integrate effectively with popular data science tools (pandas, scikit-learn, spacy, pytorch), nor efficiently with popular data engineering infrastructure such as Spark, RAPIDS, Ray, Parquet, fsspect, etc. @pacoid reviews kglab – an open source project that integrates most all of the above, and moreover provides ways to leverage disparate techniques in ways that complement each other, to produce Hybrid AI solutions for industry use cases. pod.co/the-connected-data-po… #GraphDataScience #HybridAI #DataScience #Python #KnowledgeGraphs #OpenSource #DataEngineering #Podcast #MachineLearning #GraphTechnology #AIInnovation #PythonDev #DataInfrastructure #TechInnovation #DataTech #ConnectedData

Tomaz Bratanic's book Graph Algorithms for Data Science explores the most important algorithms and techniques for graphs in data science, providing concrete advice on implementation and deployment. Alexander Erdl invited him to our live streams to discuss the book. Watch it and get a hint—you'll want to get the book! bit.ly/3BdGA6h #Neo4j #graphdatascience @tb_tomaz

We’re thrilled to introduce Adam Cowley from Neo4j as a distinguished speaker for our upcoming LLM bootcamp! 🎉 Adam will bridge the gap between Graph Data Science and Generative AI, showcasing how to leverage vector embeddings for real-world applications. Get ready to dive deep into knowledge graphs, semantic search, and much more! Don't miss the opportunity to upskill with cutting-edge knowledge: hubs.la/Q02T_3Fz0 - this is your chance to learn from the best! 💪 💡 Why attend the bootcamp? • Expert Guidance: Learn from Adam Cowley, a seasoned professional at Neo4j with extensive experience in Graph Data Science and Generative AI applications. • Skill Enhancement: Equip yourself with the ability to build and optimize LLM applications, making you a valuable asset in any tech-driven organization. • Networking Opportunities: Connect with fellow AI enthusiasts, practitioners, and industry leaders, expanding your professional network and opportunities for collaboration. • Career Advancement: By mastering cutting-edge technologies and methodologies, you position yourself at the forefront of AI and ML advancements, significantly enhancing your career prospects and professional growth. Whether you’re deep into graph analytics or just starting out, this session will equip you with the skills to unlock the potential of large-scale data and solve real-world problems. #LLMDojo #LLMs #MachineLearning #AI #LLMBootcamp #GenerativeAI #GraphDataScience #Neo4j #VectorEmbeddings #DataDrivenSolutions

Graph Algorithms for Data Science book by @tb_tomaz explores the most important algorithms and techniques for graphs in data science, providing concrete advice on implementation and deployment. Alex invited him to our live streams to discuss the book. Watch it and get a hint—you'll want to get the book! bit.ly/3BdGA6h #Neo4j #graphdatascience

For all who want to get started with #GraphDataScience, here's the ⭐ Graph Data Science For Dummies, Second Edition book! ⭐ Make better predictions with graph analytics! Download for free here: bit.ly/3R10yWz #Neo4j #datascience

✨Catch the AWS-KGC #GraphRAG Workshop this JULY 11 during #AWSSummit New York! 💫Learn about explainable responses using knowledge graphs and #RAG. Limited spots—sign up below! tinyurl.com/awskgc-ragwkshpj… #AWSKGC #knowledgegraphs #graphdatascience #NYCtech #GenerativeAI #GPT

⚠️ Read more and register for the Early Access Program: bit.ly/4c69oue #SnowflakeSummi #Snowflake #Neo4j #graphdatascience #GenAI #ML @shasbe @SnowflakeDB

For all who want to get started with #GraphDataScience, here's the ⭐ Graph Data Science For Dummies, Second Edition book! ⭐ Make better predictions with graph analytics! Download for free here: bit.ly/3R10yWz #Neo4j #datascience

OMG! My first "official" technical reviewer gig! So excited to be part of "Graph Data Science with Python & Neo4j" by @Tim___Eastridge! 👉orangeava.com/products/graph… A must-read for graph data enthusiasts! @ava_oran #GraphDataScience #Python #Neo4j #BookRelease #ProudReviewer

Join Adam on a journey to explore the ease of initiating and experimenting with Neo4j #GraphDataScience through its #Python client surface. #tbt to this #NODES2023 great talk! bit.ly/3IVihdT

🤗 Looks like we are ready to work on the left side on our #knowledgegraph and reach new levels of #knowledge on our information system thanks to @neo4j 🤗 gartner.com/en/articles/unde… #graphdatascience #llm #ai #aiadoption #learnbydoing #dowhatmatters #datadriven

⭐ Graph Data Science For Dummies, Second Edition⭐ If you want to get started with #GraphDataScience, this is the book for you.👐 Make better predictions with graph analytics! Download for free here: bit.ly/3rLTZxM #Neo4j #datascience

So happy about this! @hopsworks is partnering with @neo4j and we are hosting a series of #webinars to illustrate the synergies between #graphdatabases, #graphdatascience and #machinelearning and #ai systems. All my #graphista friends rejoice, and "see" you at the event! eventbrite.se/e/ml-driven-an…

Get the latest announcements about The Knowledge Graph Conference 2024 (May 6-10) here and on our LinkedIn Page. Stay updated on #KGC2024 speakers, talks, and sponsors by following this link 👇 linkedin.com/company/the-kno…. #KnowledgeGraphs #LinkedData #LLMs #GraphDataScience #AI

🌐 Part 2 of #AdventOfCode #AoC2023 #day1 was a deep dive into graph theory with #Neo4j! I used GDS for weakly connected components to identify subgraphs, followed by a topological sort in a DAG. 📈 Graph database for the win! #GraphDataScience